Relational database of treatment planning system information

The purpose of the present work was to develop a relational database and associated applications to facilitate retrospective review of data present in radiation treatment plans. The data source was a commercial radiation treatment planning system (Pinnacle3, Philips Medical Systems, Milpitas CA), which is specifically characterized by an open data storage format and internal scripting capability. The database is an open-source, relational database (PostgreSQL, PostgreSQL Global Development Group, http://www.postgresql.org). The data is presented through a web interface in addition to being fully query-accessible using standard tools. A database schema was created to organize the large collection of parameters used to generate treatment plans as well as the parameters that characterized these plans. The system was implemented through a combination of the treatment planning systems internal scripting language and externally executed code. Data is exported in a way that is transparent to the user, through integration into an existing and routinely-used process. The system has been transparently incorporated into our radiation treatment planning workflow. The website-based database interface has allowed users with minimal training to extract information from the database

Monte Carlo calculations and measurements of absorbed dose per monitor unit for the treatment of uveal melanoma with proton therapy

The treatment of uveal melanoma with proton radiotherapy has provided excellent clinical outcomes. However, contemporary treatment planning systems use simplistic dose algorithms that limit the accuracy of relative dose distributions. Further, absolute predictions of absorbed dose per monitor unit are not yet available in these systems. The purpose of this study was to determine if Monte Carlo methods could predict dose per monitor unit (D/MU) value at the center of a proton spread-out Bragg peak (SOBP) to within 1% on measured values for a variety of treatment fields relevant to ocular proton therapy. The MCNPX Monte Carlo transport code, in combination with realistic models for the ocular beam delivery apparatus and a water phantom, was used to calculate dose distributions and D/MU values, which were verified by the measurements. Measured proton beam data included central-axis depth dose profiles, relative cross-field profiles and absolute D/MU measurements under several combinations of beam penetration ranges and range-modulation widths. The Monte Carlo method predicted D/MU values that agreed with measurement to within 1% and dose profiles that agreed with measurement to within 3% of peak dose or within 0.5 mm distance-to-agreement. Lastly, a demonstration of the clinical utility of this technique included calculations of dose distributions and D/MU values in a realistic model of the human eye. It is possible to predict D/MU values accurately for clinical relevant range-modulated proton beams for ocular therapy using the Monte Carlo method. It is thus feasible to use the Monte Carlo method as a routine absolute dose algorithm for ocular proton therapy. © 2008 Institute of Physics and Engineering in Medicine

Determination of patient-specific internal gross tumor volumes for lung cancer using four-dimensional computed tomography

<p>Abstract</p> <p>Background</p> <p>To determine the optimal approach to delineating patient-specific internal gross target volumes (IGTV) from four-dimensional (4-D) computed tomography (CT) image data sets used in the planning of radiation treatment for lung cancers.</p> <p>Methods</p> <p>We analyzed 4D-CT image data sets of 27 consecutive patients with non-small-cell lung cancer (stage I: 17, stage III: 10). The IGTV, defined to be the envelope of respiratory motion of the gross tumor volume in each 4D-CT data set was delineated manually using four techniques: (<it>1</it>) combining the gross tumor volume (GTV) contours from ten respiratory phases (IGTV_AllPhases); (<it>2</it>) combining the GTV contours from two extreme respiratory phases (0% and 50%) (IGTV_2Phases); (<it>3</it>) defining the GTV contour using the maximum intensity projection (MIP) (IGTV_MIP); and (<it>4</it>) defining the GTV contour using the MIP with modification based on visual verification of contours in individual respiratory phase (IGTV_MIP-Modified). Using the IGTV_AllPhasesas the optimum IGTV, we compared volumes, matching indices, and extent of target missing using the IGTVs based on the other three approaches.</p> <p>Results</p> <p>The IGTV_MIPand IGTV_2Phaseswere significantly smaller than the IGTV_AllPhases(<it>p </it>< 0.006 for stage I and <it>p </it>< 0.002 for stage III). However, the values of the IGTV_MIP-Modifiedwere close to those determined from IGTV_AllPhases(<it>p </it>= 0.08). IGTV_MIP-Modifiedalso matched the best with IGTV_AllPhases.</p> <p>Conclusion</p> <p>IGTV_MIPand IGTV_2Phasesunderestimate IGTVs. IGTV_MIP-Modifiedis recommended to improve IGTV delineation in lung cancer.</p

Navigating the medical physics education and training landscape

PurposeThe education and training landscape has been profoundly reshaped by the ABR 2012/2014 initiative and the MedPhys Match. This work quantifies these changes and summarizes available reports, surveys, and statistics on education and training.MethodsWe evaluate data from CAMPEP‐accredited program websites, annual CAMPEP graduate and residency program reports, and surveys on the MedPhys Match and Professional Doctorate degree (DMP).ResultsFrom 2009–2015, the number of graduates from CAMPEP‐accredited graduate programs rose from 210 to 332, while CAMPEP‐accredited residency positions rose from 60 to 134. We estimate that approximately 60% of graduates of CAMPEP‐accredited graduate programs intend to enter clinical practice, however, only 36% of graduates were successful in acquiring a residency position in 2015. The maximum residency placement percentage for a graduate program is 70%, while the median for all programs is only 22%. Overall residency placement percentage for CAMPEP‐accredited program graduates from 2011–2015 was approximately 38% and 25% for those with a PhD and MS, respectively. The disparity between the number of clinically oriented graduates and available residency positions is perceived as a significant problem by over 70% of MedPhys Match participants responding to a post‐match survey. Approximately 32% of these respondents indicated that prior knowledge of this situation would have changed their decision to pursue graduate education in medical physics.ConclusionThese data reveal a substantial disparity between the number of residency training positions and graduate students interested in these positions, and a substantial variability in residency placement percentage across graduate programs. Comprehensive data regarding current and projected supply and demand within the medical physics workforce are needed for perspective on these numbers. While the long‐term effects of changes in the education and training infrastructure are still unclear, available survey data suggest that these changes could negatively affect potential entrants to the profession.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/139957/1/acm212202.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/139957/2/acm212202_am.pd

American Association of Physicists in Medicine Radiation Therapy Committee Task Group 53: Quality assurance for clinical radiotherapy treatment planning

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134846/1/mp8373.pd

Verifying 4D gated radiotherapy using time-integrated electronic portal imaging: a phantom and clinical study

<p>Abstract</p> <p>Background</p> <p>Respiration-gated radiotherapy (RGRT) can decrease treatment toxicity by allowing for smaller treatment volumes for mobile tumors. RGRT is commonly performed using external surrogates of tumor motion. We describe the use of time-integrated electronic portal imaging (TI-EPI) to verify the position of internal structures during RGRT delivery</p> <p>Methods</p> <p>TI-EPI portals were generated by continuously collecting exit dose data (aSi500 EPID, Portal vision, Varian Medical Systems) when a respiratory motion phantom was irradiated during expiration, inspiration and free breathing phases. RGRT was delivered using the Varian RPM system, and grey value profile plots over a fixed trajectory were used to study object positions. Time-related positional information was derived by subtracting grey values from TI-EPI portals sharing the pixel matrix. TI-EPI portals were also collected in 2 patients undergoing RPM-triggered RGRT for a lung and hepatic tumor (with fiducial markers), and corresponding planning 4-dimensional CT (4DCT) scans were analyzed for motion amplitude.</p> <p>Results</p> <p>Integral grey values of phantom TI-EPI portals correlated well with mean object position in all respiratory phases. Cranio-caudal motion of internal structures ranged from 17.5–20.0 mm on planning 4DCT scans. TI-EPI of bronchial images reproduced with a mean value of 5.3 mm (1 SD 3.0 mm) located cranial to planned position. Mean hepatic fiducial markers reproduced with 3.2 mm (SD 2.2 mm) caudal to planned position. After bony alignment to exclude set-up errors, mean displacement in the two structures was 2.8 mm and 1.4 mm, respectively, and corresponding reproducibility in anatomy improved to 1.6 mm (1 SD).</p> <p>Conclusion</p> <p>TI-EPI appears to be a promising method for verifying delivery of RGRT. The RPM system was a good indirect surrogate of internal anatomy, but use of TI-EPI allowed for a direct link between anatomy and breathing patterns.</p

Hendee's radiation therapy physics

The publication of this fourth edition, more than ten years on from the publication of Radiation Therapy Physics third edition, provides a comprehensive and valuable update to the educational offerings in this field. Led by a new team of highly esteemed authors, building on Dr Hendee’s tradition, Hendee’s Radiation Therapy Physics offers a succinctly written, fully modernised update. Radiation physics has undergone many changes in the past ten years: intensity-modulated radiation therapy (IMRT) has become a routine method of radiation treatment delivery, digital imaging has replaced film-screen imaging for localization and verification, image-guided radiation therapy (IGRT) is frequently used, in many centers proton therapy has become a viable mode of radiation therapy, new approaches have been introduced to radiation therapy quality assurance and safety that focus more on process analysis rather than specific performance testing, and the explosion in patient-and machine-related data has necessitated an increased awareness of the role of informatics in radiation therapy. As such, this edition reflects the huge advances made over the last ten years. This book: Provides state of the art content throughout Contains four brand new chapters; image-guided therapy, proton radiation therapy, radiation therapy informatics, and quality and safety improvement Fully revised and expanded imaging chapter discusses the increased role of digital imaging and computed tomography (CT) simulation The chapter on quality and safety contains content in support of new residency training requirements Includes problem and answer sets for self-test This edition is essential reading for radiation oncologists in training, students of medical physics, medical dosimetry, and anyone interested in radiation therapy physics, quality, and safety

Treatment planning using a dose–volume feasibility search algorithm

Purpose: An approach to treatment plan optimization is presented that inputs dose–volume constraints and utilizes a feasibility search algorithm that seeks a set of beam weights so that the calculated dose distributions satisfy the dose–volume constraints. In contrast to a search for the “best” plan, this approach can quickly determine feasibility and point out the most restrictive of the predetermined constraints.Methods and Materials: The cyclic subgradient projection (CSP) algorithm was modified to incorporate dose–volume constraints in a treatment plan optimization schema. The algorithm was applied to determine beam weights for several representative three-dimensional treatment plans.Results: Using the modified CSP algorithm, we found that either a feasible solution to the dose–volume constraint problem was found or the program determined, after a predetermined set of iterations was performed, that no feasible solution existed for the particular set of dose–volume constraints. If no feasible solution existed, we relaxed several of the dose–volume constraints and were able to achieve a feasible solution.Conclusion: Feasibility search algorithms can be used in radiation treatment planning to generate a treatment plan that meets the dose–volume constraints established by the radiation oncologist. In the absence of a feasible solution, these algorithms can provide information to the radiation oncologist as to how the dose–volume constraints may be modified to achieve a feasible solution

Using a dose-volume feasibility search algorithm for radiation treatment planning

The widespread use of 3-D treatment planning has prompted the need for automated techniques to assist the treatment planner in selecting suitable plans. Approaches to treatment plan optimization are based on the presumption that a computer algorithm can rapidly search through the space of beam parameters to determine those parameters that yield the best treatment plan. Procedures for treatment plan optimization consist of two components. The first component is the definition of an objective function that quantifies the desirability of a treatment plan, while the second component consists of an algorithm that maximizes (or minimizes) the objective function. While the latter task is a relatively straightforward problem in mathematical optimization and is limited by execution time and computer memory, the more difficult task is that of defining the “best” treatment plan

A serial 4DCT study to quantify range variations in charged particle radiotherapy of thoracic cancers

Weekly serial 4DCT scans were acquired under free breathing conditions to assess water equivalent pathlength (WEL) variations due to both intrafractional and interfractional changes in tissue thickness and density and to calculate proton dose distributions resulting from anatomical variations observed in serial 4DCT. A template of ROIs was defined on the anterior-posterior (AP) beam’s eye view and WEL measurements were made over these ROIs to quantify chest wall thickness variations. Interfractional proton dose distributions were calculated to assess changes in the expected dose distributions caused by range variations.Mean intrafractional chest wall WEL changes during respiration varied by: -4.1mm(<-10.2mm), -3.6 mm(<-7.1mm), -3.2mm(<-5.6mm), -2.5mm(<-5.1mm) during respiration in the ITV, upper, middle and lower lung regions respectively. The mean interfractional chest wall WEL variation at week6 decreased by -4.0mm(<-8.6mm), -9.1mm(<-17.9mm), -9.4mm(<-25.3mm), -4.5mm(<-15.6mm) in the ITV, upper, middle and lower lung regions respectively. The variations were decomposed into anterior and posterior chest wall thickness changes. Dose overshoot beyond the target was observed when the initial boli was applied throughout the treatment course. This overshoot is due to chest wall thickness variations and target positional variations.The radiological pathlength can vary significantly during respiration as well as over the course of several weeks of charged particle therapy. Intrafractional/interfractional chest wall thickness changes can be a significant source of range variation in treatment of lung tumors with charged particle beams, resulting in dose distribution perturbations from the initial plan. Consideration of these range variations should be considered in choosing the therapeutic charged particle beam range